text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> :param obj: input object
:return: Serializer
"""
# 1-NULL serializer
if obj is None:
return self._null_serializer_adapter
obj_type = type(obj)
serializer = None
# 2-Default serializers, Dataserializable, Portable, primitives, ar... | code_fim | hard | {
"lang": "python",
"repo": "mustafaiman/hazelcast-python-client",
"path": "/hazelcast/serialization/base.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mustafaiman/hazelcast-python-client path: /hazelcast/serialization/base.py
from threading import RLock
from api import *
from data import *
from hazelcast.core import *
from serializer import *
EMPTY_PARTITIONING_STRATEGY = lambda key: None
def handle_exception(e):
if isinstance(e, Memory... | code_fim | hard | {
"lang": "python",
"repo": "mustafaiman/hazelcast-python-client",
"path": "/hazelcast/serialization/base.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> serializer_adaptor = create_buffer_serializer_wrapper(serializer)
self.register_constant_serializer_adaptor(obj_type, serializer_adaptor)
def register_constant_serializer_adaptor(self, obj_type, serializer_adaptor):
self._constant_type_dict[obj_type] = serializer_adaptor
... | code_fim | hard | {
"lang": "python",
"repo": "mustafaiman/hazelcast-python-client",
"path": "/hazelcast/serialization/base.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Logs epoch level validation metrics."""
self.log_dict(self.val_metrics.compute())
self.val_metrics.reset()
def test_step(self, *args: Any, **kwargs: Any) -> None:
"""Compute test loss.
Args:
batch: the output of your DataLoader
"""
... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/torchgeo",
"path": "/torchgeo/trainers/segmentation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Logs epoch level test metrics."""
self.log_dict(self.test_metrics.compute())
self.test_metrics.reset()
def predict_step(self, *args: Any, **kwargs: Any) -> Tensor:
"""Compute and return the predictions.
By default, this will loop over images in a dataloader... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/torchgeo",
"path": "/torchgeo/trainers/segmentation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: microsoft/torchgeo path: /torchgeo/trainers/segmentation.py
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""Segmentation tasks."""
import os
import warnings
from typing import Any, cast
import matplotlib.pyplot as plt
import segmentation_models_... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/torchgeo",
"path": "/torchgeo/trainers/segmentation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vmware/network-insight-sdk-generic-datasources path: /network_insight_sdk_generic_datasources/common/import_module_utilities.py
# Copyright 2019 VMware, Inc.
# SPDX-License-Identifier: BSD-2-Clause
import importlib
def load_class(class_path):
module = importlib.import_module(".".join(clas... | code_fim | hard | {
"lang": "python",
"repo": "vmware/network-insight-sdk-generic-datasources",
"path": "/network_insight_sdk_generic_datasources/common/import_module_utilities.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def load_class_for_pre_post_parser(device, class_name):
module_path = "{0}.{1}.{1}_{2}".format("network_insight_sdk_generic_datasources.routers_and_switches", device,
"pre_post_processor")
module = importlib.import_module(module_path)
return getattr(... | code_fim | hard | {
"lang": "python",
"repo": "vmware/network-insight-sdk-generic-datasources",
"path": "/network_insight_sdk_generic_datasources/common/import_module_utilities.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def load_class_for_process_table(device, class_name):
module_path = "{0}.{1}.{1}_{2}".format("network_insight_sdk_generic_datasources.routers_and_switches", device,
"pre_post_processor")
module = importlib.import_module(module_path)
return getattr(mod... | code_fim | hard | {
"lang": "python",
"repo": "vmware/network-insight-sdk-generic-datasources",
"path": "/network_insight_sdk_generic_datasources/common/import_module_utilities.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tnakamura/SilverTask path: /silvertask-web/kay/sessions/middleware.py
# -*- coding: utf-8 -*-
"""
Kay session middleware.
:Copyright: (c) 2009 Accense Technology, Inc. All rights reserved.
:license: BSD, see LICENSE for more details.
"""
import kay.sessions
from kay.conf import settings
from w... | code_fim | medium | {
"lang": "python",
"repo": "tnakamura/SilverTask",
"path": "/silvertask-web/kay/sessions/middleware.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if hasattr(request, '_cached_session') and \
request.session.should_save and hasattr(response, 'set_cookie'):
session_store = import_string(settings.SESSION_STORE)()
session_store.save(request.session)
response.set_cookie(settings.COOKIE_NAME,
sess... | code_fim | hard | {
"lang": "python",
"repo": "tnakamura/SilverTask",
"path": "/silvertask-web/kay/sessions/middleware.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: great-expectations/great_expectations path: /great_expectations/core/usage_statistics/schemas.py
"$schema": SCHEMA,
"title": "anonymized-test-yaml-config-payload",
"definitions": {
"anonymized_string": anonymized_string_schema,
"anonymized_class_info": anonymized_class_inf... | code_fim | hard | {
"lang": "python",
"repo": "great-expectations/great_expectations",
"path": "/great_expectations/core/usage_statistics/schemas.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>anonymized_expectation_configuration_builder_schema = {
"$schema": SCHEMA,
"title": "anonymized-expectation-configuration-builder",
"definitions": {
"anonymized_string": anonymized_string_schema,
},
"type": "object",
"properties": {
"parent_class": {"type": "string"... | code_fim | hard | {
"lang": "python",
"repo": "great-expectations/great_expectations",
"path": "/great_expectations/core/usage_statistics/schemas.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mpavezb/CarND-Advanced-Lane-Lines path: /main.py
from src.logger import Log
from src.lane_tracker import LaneLinesTracker
from examples import *
<|fim_suffix|> input_file = "project_video.mp4"
output_file = "output_videos/project_video.mp4"
tracker = LaneLinesTracker()
clip = tra... | code_fim | medium | {
"lang": "python",
"repo": "mpavezb/CarND-Advanced-Lane-Lines",
"path": "/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Log.debug_enabled = False
# RunCalibrationExample()
# RunDistortionCorrectionExample()
# RunEdgeDetectionExample()
# RunPerspectiveTransformExample()
# RunLaneFittingExample()
# RunFullPipelineExample()
ProcessProjectVideo(subclip_seconds=None)
if __name__ == "__main__":... | code_fim | hard | {
"lang": "python",
"repo": "mpavezb/CarND-Advanced-Lane-Lines",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>qs = MyModel.objects
qs = q.filter(field__regex=r'^(An?|The) +')<|fim_prefix|># repo: andrewp-as-is/django-examples path: /Models/querysets/Field lookups/__regex/tests.py
#!/usr/bin/env python
from .models import MyModel
<|fim_middle|>"""
https://docs.djangoproject.com/en/dev/ref/models/querysets/#regex... | code_fim | medium | {
"lang": "python",
"repo": "andrewp-as-is/django-examples",
"path": "/Models/querysets/Field lookups/__regex/tests.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andrewp-as-is/django-examples path: /Models/querysets/Field lookups/__regex/tests.py
#!/usr/bin/env python
from .models import MyModel
<|fim_suffix|>qs = MyModel.objects
qs = q.filter(field__regex=r'^(An?|The) +')<|fim_middle|>"""
https://docs.djangoproject.com/en/dev/ref/models/querysets/#regex... | code_fim | medium | {
"lang": "python",
"repo": "andrewp-as-is/django-examples",
"path": "/Models/querysets/Field lookups/__regex/tests.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KKowalewski24/MUM path: /Task4/Program/module/k_means.py
from datetime import datetime
from typing import List, Tuple
import matplotlib.pyplot as plt
import numpy as np
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_score
from module.LatexGenerator import LatexGenerat... | code_fim | hard | {
"lang": "python",
"repo": "KKowalewski24/MUM",
"path": "/Task4/Program/module/k_means.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> save_latex: bool = False) -> None:
scores_clusters_numbers: List[Tuple[List[float], List[float]]] = []
scores_iter_numbers: List[Tuple[List[float], List[float]]] = []
for cluster_value in CLUSTERS_NUMBER:
k_means = KMeans(
n_clusters=cluster_value
... | code_fim | hard | {
"lang": "python",
"repo": "KKowalewski24/MUM",
"path": "/Task4/Program/module/k_means.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: r3gh/hackathonRioHeatMap path: /server/tweets/src/stream_twitter.py
import tweepy
from tweepy import OAuthHandler
from tweepy.streaming import StreamListener
import numpy as np
import json
import numpy as np
from tweets.src.functions import *
class StreamTwitterGenerator:
def __init__(self):
... | code_fim | medium | {
"lang": "python",
"repo": "r3gh/hackathonRioHeatMap",
"path": "/server/tweets/src/stream_twitter.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> consumer_key = tokens['consumer_key']
consumer_secret = tokens['consumer_secret']
access_token = tokens['access_token']
access_secret = tokens['access_secret']
auth = OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_secret)
api = ... | code_fim | medium | {
"lang": "python",
"repo": "r3gh/hackathonRioHeatMap",
"path": "/server/tweets/src/stream_twitter.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> soup = htmlRequest(url)
genreList = soup.select('.breadcrumb > li')[1].contents[1]
genreName = genreList.contents[0]
return genreName
"""
# Functions which are 3 functions below from here gives exact URL
# however it is little bit slower
"""
def getCatIDLetters(l,url):
i = url.rfind("id")
catID =... | code_fim | hard | {
"lang": "python",
"repo": "ferhatyaman/appStore",
"path": "/appReader.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ferhatyaman/appStore path: /appReader.py
import urllib.request
from bs4 import BeautifulSoup
import string, sys, sqlite3, time
#if connection lost or server waits the program
#try to catch error and sleep until error is gone
def htmlRequest(url):
success= False
while not success:
tr... | code_fim | hard | {
"lang": "python",
"repo": "ferhatyaman/appStore",
"path": "/appReader.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 1748276037/Django path: /bookmanager/book/views.py
from django.shortcuts import render
<|fim_suffix|> context = {
'name':'想了解更多吗?点击我哦'
}
# 请求
# 参数2: 模板文件
return render(request,'book/index.html',context=context)<|fim_middle|># Create your views here.
from django.http i... | code_fim | medium | {
"lang": "python",
"repo": "1748276037/Django",
"path": "/bookmanager/book/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> context = {
'name':'想了解更多吗?点击我哦'
}
# 请求
# 参数2: 模板文件
return render(request,'book/index.html',context=context)<|fim_prefix|># repo: 1748276037/Django path: /bookmanager/book/views.py
from django.shortcuts import render
<|fim_middle|># Create your views here.
from django.http i... | code_fim | medium | {
"lang": "python",
"repo": "1748276037/Django",
"path": "/bookmanager/book/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Fourier transform
fft2 = staticmethod(npa.fft.fft2)
backend = NumpyBackend()
def set_backend(name):
"""
Set the backend for the simulations.
This function monkey-patches the backend object by changing its class.
This way, all methods of the backend object will be replace... | code_fim | hard | {
"lang": "python",
"repo": "SiEPIC/legume",
"path": "/legume/backend.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SiEPIC/legume path: /legume/backend.py
"""
Backend for the simulations. Available backends:
- numpy [default]
- autograd
A backend can be set with the 'set_backend'
import legume
legume.set_backend("autograd")
Numpy is still used with some functionalities; if autograd backend is set,
... | code_fim | hard | {
"lang": "python",
"repo": "SiEPIC/legume",
"path": "/legume/backend.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ably/ably-python path: /ably/types/options.py
import random
import logging
from ably.transport.defaults import Defaults
from ably.types.authoptions import AuthOptions
log = logging.getLogger(__name__)
class Options(AuthOptions):
def __init__(self, client_id=None, log_level=0, tls=True, re... | code_fim | hard | {
"lang": "python",
"repo": "ably/ably-python",
"path": "/ably/types/options.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def loop(self):
return self.__loop
# RTC1b
@property
def auto_connect(self):
return self.__auto_connect
@property
def connection_state_ttl(self):
return self.__connection_state_ttl
@connection_state_ttl.setter
def connection_state_tt... | code_fim | hard | {
"lang": "python",
"repo": "ably/ably-python",
"path": "/ably/types/options.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tiabas/django-forms path: /form_engine/views.py
for_field_type(field_type)
if not template_field_form:
raise HttpResponseNotFound("<p>Invalid field type: </p>" % request.POST.get('qtype'))
form_template = get_object_or_404(Survey, pk=form_id)
item_forms = forms_for_survey_no_prefix(request, ... | code_fim | hard | {
"lang": "python",
"repo": "tiabas/django-forms",
"path": "/form_engine/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Displays page for creating or editing a form template
"""
form_template = get_object_or_404(Survey, pk=form_id)
# if form_template.has_answers:
# return HttpResponse("Template cannot be edited because it has data attached to it")
form_template.update_form = SurveyModelForm(instance=form_templa... | code_fim | hard | {
"lang": "python",
"repo": "tiabas/django-forms",
"path": "/form_engine/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tiabas/django-forms path: /form_engine/views.py
rse('form_template_edit', kwargs={'form_id': form_template.id}))
@login_required
def question_get(request,form_id):
if request.method == "GET":
request_get = request.GET.copy()
question = Question.objects.get(id=request_get['q_id'], survey=for... | code_fim | hard | {
"lang": "python",
"repo": "tiabas/django-forms",
"path": "/form_engine/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.parsedstring = unparsedstring
self.parsed = False<|fim_prefix|># repo: xl-sec/securityheaders path: /securityheaders/models/xpoweredby/xpoweredby.py
from securityheaders.models import Header
from securityheaders.models.annotations import *
@description('Header describing the server ... | code_fim | medium | {
"lang": "python",
"repo": "xl-sec/securityheaders",
"path": "/securityheaders/models/xpoweredby/xpoweredby.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, unparsedstring):
self.parsedstring = unparsedstring
self.parsed = False<|fim_prefix|># repo: xl-sec/securityheaders path: /securityheaders/models/xpoweredby/xpoweredby.py
from securityheaders.models import Header
from securityheaders.models.annotations import *
@de... | code_fim | easy | {
"lang": "python",
"repo": "xl-sec/securityheaders",
"path": "/securityheaders/models/xpoweredby/xpoweredby.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xl-sec/securityheaders path: /securityheaders/models/xpoweredby/xpoweredby.py
from securityheaders.models import Header
from securityheaders.models.annotations import *
<|fim_suffix|> def __init__(self, unparsedstring):
self.parsedstring = unparsedstring
self.parsed = False<|f... | code_fim | hard | {
"lang": "python",
"repo": "xl-sec/securityheaders",
"path": "/securityheaders/models/xpoweredby/xpoweredby.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Load the elevation DEM
# Terrainfile is set in config.py
dem = xr.open_dataset(terrainfile)
dem = dem.rename({'latitude':'lat', 'longitude':'lon'})
demlats = dem['lat']
demlons = dem['lon']
final_lats = prism_grid.lat.values
final_lons = prism_grid.lon.values
#... | code_fim | hard | {
"lang": "python",
"repo": "m-wessler/wxdisco-tools",
"path": "/funcs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: m-wessler/wxdisco-tools path: /funcs.py
# the old fashioned way first...
curlcommand = 'curl -s -m {} -o {} {}'.format(timeout, fpath, url)
call(curlcommand, shell=True)
try:
fsize = stat(fpath).st_size
except:
print('FILE NOT F... | code_fim | hard | {
"lang": "python",
"repo": "m-wessler/wxdisco-tools",
"path": "/funcs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: m-wessler/wxdisco-tools path: /funcs.py
* pclimo2
return pclimo
def downscale_prism(init_time, forecast_time):
import warnings
warnings.filterwarnings("ignore")
from scipy import ndimage
from pandas import to_datetime
from datetime import datetime, timedelta
... | code_fim | hard | {
"lang": "python",
"repo": "m-wessler/wxdisco-tools",
"path": "/funcs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SeaWar741/ITC path: /MLH/CursoAWS/eventbrite.py
import config # 💡importing our env variables from dotenv
from urllib.request import Request, urlopen # 💡open a web url
from urllib.parse import quote # 💡get rid of any weird characters in our city string
import json # 💡json stands for Javasc... | code_fim | hard | {
"lang": "python",
"repo": "SeaWar741/ITC",
"path": "/MLH/CursoAWS/eventbrite.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # 3. 🆘✨we want to get a JSON response from Eventbrite.
# They keep the info we need in the response_body.events. Help us get the data we want!
events = json.loads(response_body)["FIX_ME"]
# 💡returns a JSON array of events in a city
return events<|fim_prefix|># repo: SeaWar741/... | code_fim | hard | {
"lang": "python",
"repo": "SeaWar741/ITC",
"path": "/MLH/CursoAWS/eventbrite.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: openwater/h2o-really path: /openwater/context_processors.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from django.contrib.sites.models import get_current_site
<|fim_suffix|> current_site = get_current_site(request)
return {
'site': current_site
}<|fim_middle|>
def site(req... | code_fim | easy | {
"lang": "python",
"repo": "openwater/h2o-really",
"path": "/openwater/context_processors.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> current_site = get_current_site(request)
return {
'site': current_site
}<|fim_prefix|># repo: openwater/h2o-really path: /openwater/context_processors.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from django.contrib.sites.models import get_current_site
<|fim_middle|>def site(req... | code_fim | easy | {
"lang": "python",
"repo": "openwater/h2o-really",
"path": "/openwater/context_processors.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pjanis/funtool path: /funtool/state.py
# Defines of a state
import collections
State = collections.namedtuple('State',['id','data','measures','meta','groupings'] )
# A state is the basic unit of analysis. It can be anything that can be coerced into the given form,
# though most measures will a... | code_fim | hard | {
"lang": "python",
"repo": "pjanis/funtool",
"path": "/funtool/state.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# META
#=====
#
# These are useful meta pairs. They are not neccessary for all states. These are only recommended usages.
#
#-----
# database_id a dict which contains three values that identify the state in a database
# The three values are:
# table_name the table that identifies t... | code_fim | hard | {
"lang": "python",
"repo": "pjanis/funtool",
"path": "/funtool/state.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_get_one_hot_vectorizer(self):
"""
Asserts ml4ir.base.features.preprocessing.get_one_hot_vectorizer
"""
feature_info = {
"name": "categorical_variable",
"feature_layer_info": {
"fn": "categorical_indicator_with_vocabulary_... | code_fim | hard | {
"lang": "python",
"repo": "salesforce/ml4ir",
"path": "/python/ml4ir/base/tests/test_feature_processing.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> typ = 'float'
label_vector = np.ones(10, dtype=typ)
label_vector[0] = 5
label_vector[-1] = 5
label_vector = tf.convert_to_tensor(label_vector)
clicks = preprocessing.convert_label_to_clicks(label_vector, typ)
assert clicks[0] == 1 and clicks[-1] == 1... | code_fim | hard | {
"lang": "python",
"repo": "salesforce/ml4ir",
"path": "/python/ml4ir/base/tests/test_feature_processing.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: salesforce/ml4ir path: /python/ml4ir/base/tests/test_feature_processing.py
import string
from ml4ir.applications.ranking.tests.test_base import RankingTestBase
from ml4ir.base.features import preprocessing
import tensorflow as tf
import numpy as np
class RankingModelTest(RankingTestBase):
... | code_fim | hard | {
"lang": "python",
"repo": "salesforce/ml4ir",
"path": "/python/ml4ir/base/tests/test_feature_processing.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #I am expecting IoU to have dimenssions [n_targets, n_predictions]
true_ind = np.arange(IoU.shape[0])
pred_ind = np.argmax(IoU, axis = 1)
IoU_matches = IoU[true_ind, pred_ind]
ind_sorted = np.argsort(IoU_matches)[::-1]
IoU_matches, pred_ind, true_ind = [x[ind_sorted] for x in ... | code_fim | hard | {
"lang": "python",
"repo": "ver228/cell_localization",
"path": "/cell_localization/evaluation/segmentation_mask.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> chain_approx = cv2.CHAIN_APPROX_SIMPLE if chain_approx else cv2.CHAIN_APPROX_NONE
n_labs, seg_mask, stats, centroids = cv2.connectedComponentsWithStats(seg_mask.astype(np.uint8), 4)
kernel = cv2.getStructuringElement( cv2.MORPH_ELLIPSE, (kernel_size, kernel_size))
mm = ... | code_fim | hard | {
"lang": "python",
"repo": "ver228/cell_localization",
"path": "/cell_localization/evaluation/segmentation_mask.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ver228/cell_localization path: /cell_localization/evaluation/segmentation_mask.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: avelinojaver
"""
import cv2
import numpy as np
def get_masks_metrics(true_cells_mask, pred_cells_mask):
n_true, true_seg_mask, true_stats, tru... | code_fim | hard | {
"lang": "python",
"repo": "ver228/cell_localization",
"path": "/cell_localization/evaluation/segmentation_mask.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> parser = argparse.ArgumentParser()
parser.add_argument('--input', type=str, required=True,
help='Path to the image.')
parser.add_argument('--output_folder', type=str, default='results',
help='Path to the output file')
parser.add_argument('--o... | code_fim | medium | {
"lang": "python",
"repo": "lyx-x/nnimgproc",
"path": "/samples/denoising/process.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lyx-x/nnimgproc path: /samples/denoising/process.py
#!/usr/bin/python3
# Noise demonstration: test noise generator
import argparse
import logging
import os
from nnimgproc.target_processor.denoising import DenoisingTargetProcessor
from nnimgproc.util.image import read, write
def main():
<|fim... | code_fim | hard | {
"lang": "python",
"repo": "lyx-x/nnimgproc",
"path": "/samples/denoising/process.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> write(image=x, path=os.path.join(args.output_folder, args.output_image))
meta.save(path=os.path.join(args.output_folder, args.output_meta))
logging.info("Finish processing %s" % args.input)
if __name__ == '__main__':
main()<|fim_prefix|># repo: lyx-x/nnimgproc path: /samples/denoising/p... | code_fim | hard | {
"lang": "python",
"repo": "lyx-x/nnimgproc",
"path": "/samples/denoising/process.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> destination, predecessor = initialize(graph, source)
for i in range(len(graph)-1):
for u in graph:
for v in graph[u]:
relax(u, v, graph, destination, predecessor)
for u in graph:
for v in graph[u]:
return(retrace_negative_loop(predecessor, source))
return None
paths = []
graph = curr... | code_fim | hard | {
"lang": "python",
"repo": "solobeton99/forex-arbitrage",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: solobeton99/forex-arbitrage path: /main.py
import requests, json, math
CURRENCIES = {'GBP', 'USD', 'JPY', 'EUR'}
API_KEY = ''
class Node(object):
def __init__(self, currency_id, CURRENCIES):
super(Node, self).__init__()
self.id = currency_id
self.childs = []
for id in CURRENCIES:
i... | code_fim | hard | {
"lang": "python",
"repo": "solobeton99/forex-arbitrage",
"path": "/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Imperial-visualizations/Physics-Visualizations path: /visuals_EM/Waves and Dielectrics/plotly_arrows.py
import numpy as np
import plotly.graph_objs as go
def p2c(r, theta, phi):
"""Convert polar unit vector to cartesians"""
return [r * np.sin(theta) * np.cos(phi),
r * np.sin(... | code_fim | hard | {
"lang": "python",
"repo": "Imperial-visualizations/Physics-Visualizations",
"path": "/visuals_EM/Waves and Dielectrics/plotly_arrows.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Finds polar coordinates of arrowhead wing ends"""
frac = 0.1
r = 0.5
sin45 = np.sin(np.pi / 4.)
if self.out == True:
d = r - frac * sin45
elif self.out == False:
d = r + frac * sin45
else:
raise TypeError("arg:... | code_fim | hard | {
"lang": "python",
"repo": "Imperial-visualizations/Physics-Visualizations",
"path": "/visuals_EM/Waves and Dielectrics/plotly_arrows.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ephes/django-cast path: /cast/models/theme.py
from pathlib import Path
from django.conf import settings
from django.db import models
from django.template import engines
from django.template.loaders.base import Loader as BaseLoader
from django.utils.translation import gettext_lazy as _
from wagta... | code_fim | hard | {
"lang": "python",
"repo": "ephes/django-cast",
"path": "/cast/models/theme.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class TemplateName(models.TextChoices):
BOOTSTRAP4 = "bootstrap4", _("Bootstrap 4")
PLAIN = "plain", _("Just HTML")
def get_template_base_dir_choices() -> list[tuple[str, str]]:
"""
Return a list of choices for the template base directory setting.
"""
# handle predefined choices
... | code_fim | hard | {
"lang": "python",
"repo": "ephes/django-cast",
"path": "/cast/models/theme.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@register_setting
class TemplateBaseDirectory(BaseSiteSetting):
"""
The base directory for templates. Makes it possible to use different
templates for different sites / change look and feel of the site from
the wagtail admin.
"""
name = models.CharField(
choices=get_templ... | code_fim | hard | {
"lang": "python",
"repo": "ephes/django-cast",
"path": "/cast/models/theme.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Maskime/complex-extract path: /src/database/models.py
from peewee import *
db = SqliteDatabase("complex_extract.db")
def current_db():
<|fim_suffix|> db.create_tables([Torrent])
class Torrent(Model):
pk = AutoField()
deluge_id = CharField()
name = CharField()
... | code_fim | easy | {
"lang": "python",
"repo": "Maskime/complex-extract",
"path": "/src/database/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> class Meta:
database = db<|fim_prefix|># repo: Maskime/complex-extract path: /src/database/models.py
from peewee import *
db = SqliteDatabase("complex_extract.db")
def current_db():
return db
def initialize_db():
db.create_tables([Torrent])
class Torrent(Model):
... | code_fim | medium | {
"lang": "python",
"repo": "Maskime/complex-extract",
"path": "/src/database/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: barretobrock/slacktools path: /tests/test_db_eng.py
from unittest import (
TestCase,
main,
)
from slacktools.db_engine import (
PSQLClient,
SQLiteClient,
)
from .common import (
get_test_logger,
make_patcher,
)
class TestPSQLClient(TestCase):
@classmethod
def ... | code_fim | hard | {
"lang": "python",
"repo": "barretobrock/slacktools",
"path": "/tests/test_db_eng.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_session_mgr(self):
for eng in [self.ps_eng, self.sl_eng]:
# Normal ops
with eng.session_mgr():
self.mock_sessionmacher().assert_called()
self.mock_sessionmacher()().commit.assert_called()
self.mock_sessionmacher()().close... | code_fim | hard | {
"lang": "python",
"repo": "barretobrock/slacktools",
"path": "/tests/test_db_eng.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @query_id.setter
def query_id(self, value):
self._query_id = value
@property
def scene_code(self):
return self._scene_code
@scene_code.setter
def scene_code(self, value):
self._scene_code = value
@property
def search_src(self):
return self._... | code_fim | hard | {
"lang": "python",
"repo": "alipay/alipay-sdk-python-all",
"path": "/alipay/aop/api/domain/IntentQueryRequest.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alipay/alipay-sdk-python-all path: /alipay/aop/api/domain/IntentQueryRequest.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
from alipay.aop.api.constant.ParamConstants import *
class IntentQueryRequest(object):
def __init__(self):
self._action_src = None
self... | code_fim | hard | {
"lang": "python",
"repo": "alipay/alipay-sdk-python-all",
"path": "/alipay/aop/api/domain/IntentQueryRequest.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #print(o.output_bim)
bim.write_pickle(r'../tests/epjson_to_bim_map/detached_house.pickle')
bim.write_json(r'../tests/epjson_to_bim_map/detached_house.json')
bim.write_graphml(r'../tests/epjson_to_bim_map/detached_house.graphml')<|fim_prefix|># repo: building-energy/uSim2018_Paper29 path: ... | code_fim | medium | {
"lang": "python",
"repo": "building-energy/uSim2018_Paper29",
"path": "/analysis/openbuilding/epjson_to_bim_map.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: building-energy/uSim2018_Paper29 path: /analysis/openbuilding/epjson_to_bim_map.py
# -*- coding: utf-8 -*-
import pandas as pd
try:
from .bim_graph import BimGraph
except ImportError:
from bim_graph import BimGraph
try:
from .schedules import YearSchedule,PeriodSchedule,WeekSch... | code_fim | hard | {
"lang": "python",
"repo": "building-energy/uSim2018_Paper29",
"path": "/analysis/openbuilding/epjson_to_bim_map.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: danim1236/JA-POLS path: /2_learning/Alignment/Alignment_learning.py
from __future__ import division, print_function
import os
import shutil
import torch
import torch.optim as optim
import torchvision
from Alignment.data import get_datasets
from Alignment.nets import initialize_model
from Alignmen... | code_fim | hard | {
"lang": "python",
"repo": "danim1236/JA-POLS",
"path": "/2_learning/Alignment/Alignment_learning.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> feature_extract = config.regress_trans['feature_extract'] # Flag for feature extracting. When False, we finetune the whole model, when True we only update the reshaped layer params
# ------- Done Setting Training parameters. -------
# ------- Start running the network: ---------------
... | code_fim | hard | {
"lang": "python",
"repo": "danim1236/JA-POLS",
"path": "/2_learning/Alignment/Alignment_learning.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# Create dataloaders
dataloaders_dict = {'train': torch.utils.data.DataLoader(train_ds, batch_size=batch_size, shuffle=True),
'val': torch.utils.data.DataLoader(val_ds, batch_size=batch_size, shuffle=True)}
# Train model:
# Send the model to GPU
model_ft = mod... | code_fim | hard | {
"lang": "python",
"repo": "danim1236/JA-POLS",
"path": "/2_learning/Alignment/Alignment_learning.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bourdenas/troll path: /pytroll/audio.py
import pytroll.actions
import troll
def PlayMusic(track_id, repeat=1):
action = pytroll.actions.PlayAudio(track_id=track_id, repeat=repeat)
troll.execute(action.SerializeToString())
def StopMusic():
action = pytroll.actions.StopAudio()
t... | code_fim | hard | {
"lang": "python",
"repo": "bourdenas/troll",
"path": "/pytroll/audio.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def PauseSfx(sfx_id):
action = pytroll.actions.PauseAudio(sfx_id=sfx_id)
troll.execute(action.SerializeToString())
def ResumeSfx(sfx_id):
action = pytroll.actions.ResumeAudio(sfx_id=sfx_id)
troll.execute(action.SerializeToString())<|fim_prefix|># repo: bourdenas/troll path: /pytroll/aud... | code_fim | medium | {
"lang": "python",
"repo": "bourdenas/troll",
"path": "/pytroll/audio.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def ResumeSfx(sfx_id):
action = pytroll.actions.ResumeAudio(sfx_id=sfx_id)
troll.execute(action.SerializeToString())<|fim_prefix|># repo: bourdenas/troll path: /pytroll/audio.py
import pytroll.actions
import troll
def PlayMusic(track_id, repeat=1):
action = pytroll.actions.PlayAudio(track_... | code_fim | hard | {
"lang": "python",
"repo": "bourdenas/troll",
"path": "/pytroll/audio.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nathuffman97/flights path: /src/data_scraping/__apis__/qpx.py
import os
import json
from datetime import date
import requests
class QPX:
def __init__(self, data_path):
self.data_path = data_path
self._url_api = self._get_api_url()
self.header = {'Content-ty... | code_fim | hard | {
"lang": "python",
"repo": "nathuffman97/flights",
"path": "/src/data_scraping/__apis__/qpx.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _add_flight_data(self, ret, segment):
ret['flight_code'].append(segment['flight']['carrier'] + segment['flight']['number'])
leg = segment['leg'][0]
ret['airports'].extend([leg['origin'], leg['destination']])
ret['depart_times'].append(leg['departureTime'])
... | code_fim | hard | {
"lang": "python",
"repo": "nathuffman97/flights",
"path": "/src/data_scraping/__apis__/qpx.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MAECProject/python-maec path: /scripts/maec_4.0.1_to_4.1.py
# MAEC 4.0.1 to MAEC 4.1 Converter Script
# Translates a MAEC 4.0.1 Package or Bundle into a valid MAEC 4.1 Package or Bundle
import sys
import os
import shutil
import argparse
import maec
from maec.bundle.bundle import Bundle
... | code_fim | hard | {
"lang": "python",
"repo": "MAECProject/python-maec",
"path": "/scripts/maec_4.0.1_to_4.1.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> args = parser.parse_args()
if args.directory:
for filename in os.listdir(args.directory):
print filename
if '.xml' not in filename:
pass
elif '_report.maec-4.0.1' not in filename:
update_maec(os.path.join(args.dir... | code_fim | hard | {
"lang": "python",
"repo": "MAECProject/python-maec",
"path": "/scripts/maec_4.0.1_to_4.1.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Setup the argument parser
parser = argparse.ArgumentParser(
description='MAEC 4.0.1 --> MAEC 4.1 XML Converter Utility'
)
mutex_group = parser.add_mutually_exclusive_group(required=True)
required_name = parser.add_argument_group('required arguments')
mutex_group.add... | code_fim | hard | {
"lang": "python",
"repo": "MAECProject/python-maec",
"path": "/scripts/maec_4.0.1_to_4.1.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get(self, request, *args, **kwargs):
"Access aggregate information about entities as they occur in regulations.gov data."
results = Entity.objects(id=kwargs['entity_id'])
if not results:
raise Http404('Docket not found.')
entity = results[0]
# ... | code_fim | hard | {
"lang": "python",
"repo": "LIICornell/sparerib",
"path": "/sparerib_api/views.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LIICornell/sparerib path: /sparerib_api/views.py
': 'RTF', 'wp8': 'Word Perfect'}
class DocumentView(APIView):
"Regulations.gov document view"
def get(self, request, *args, **kwargs):
"Access basic metadata about regulations.gov documents."
results = list(Doc.objects(id=k... | code_fim | hard | {
"lang": "python",
"repo": "LIICornell/sparerib",
"path": "/sparerib_api/views.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LIICornell/sparerib path: /sparerib_api/views.py
tedView(APIView):
"Regulations.gov docket view"
def get(self, request, *args, **kwargs):
"Access basic metadata about regulations.gov dockets."
results = list(self.aggregation_class.objects(id=kwargs[self.aggregation_field... | code_fim | hard | {
"lang": "python",
"repo": "LIICornell/sparerib",
"path": "/sparerib_api/views.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> logits_data, _, _ = disc_model(preprocess(samples), WEs, BEs, WFCS, BFCS, WY, BY, WC, BC, False)
cost_sample = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits=logits_data, labels=tf.constant(1.0, shape=[FLAGS.batch_size, 1])))
contrastive_samples = gen_model(z_vecs, WPJ, BPJ, WGs, BGs... | code_fim | hard | {
"lang": "python",
"repo": "stereoboy/generative_adversarial",
"path": "/infogan_mnist.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stereoboy/generative_adversarial path: /infogan_mnist.py
d(relued, WEs[1], strides=[1, 2, 2, 1], padding='SAME')
conved = tf.nn.bias_add(conved, BEs[1])
normalized = batch_norm_layer(conved, "discriminator/bne1", reuse)
relued = leaky_relu(normalized)
# flat 1-d vectors
ch_size = FLAG... | code_fim | hard | {
"lang": "python",
"repo": "stereoboy/generative_adversarial",
"path": "/infogan_mnist.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # initialize weights, biases for Generator
# shape=[kernel_size, kernel_size, (!)out_ch_size, (!)in_ch_size] for conv2d_transposed
kernel_size = 5
WGs = [
tf.get_variable('g_conv_0', shape = [kernel_size, kernel_size, 64, 128], initializer=init_with_normal()),
tf.get_variable('g_conv_1... | code_fim | hard | {
"lang": "python",
"repo": "stereoboy/generative_adversarial",
"path": "/infogan_mnist.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pmontalb/MarkovModels path: /StochasticModels/ClosedFormModels/CHullWhiteModel.py
from math import exp
def discount_factor_observed_at(observation_date,
valuation_date, maturity, k, sigma, reference_curve):
"""
:param observation_date:
:param valuatio... | code_fim | hard | {
"lang": "python",
"repo": "pmontalb/MarkovModels",
"path": "/StochasticModels/ClosedFormModels/CHullWhiteModel.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> forward_rate = reference_curve.instantaneous_forward_rate(days_to_maturity)
forward_rate_plus = reference_curve.instantaneous_forward_rate(days_to_maturity + 1.0)
forward_rate_minus = reference_curve.instantaneous_forward_rate(days_to_maturity - 1.0)
one_day = 1.0 / 365
forward_rate_d... | code_fim | hard | {
"lang": "python",
"repo": "pmontalb/MarkovModels",
"path": "/StochasticModels/ClosedFormModels/CHullWhiteModel.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rimvaliulin/termssrv path: /termssrv/terms/urls.py
from rest_framework.routers import Default<|fim_suffix|>ks', BookViewSet)
urlpatterns = router.urls<|fim_middle|>Router
from .views import BookViewSet
router = DefaultRouter()
router.register('boo | code_fim | medium | {
"lang": "python",
"repo": "rimvaliulin/termssrv",
"path": "/termssrv/terms/urls.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ter = DefaultRouter()
router.register('books', BookViewSet)
urlpatterns = router.urls<|fim_prefix|># repo: rimvaliulin/termssrv path: /termssrv/terms/urls.py
from rest_framework.routers import Default<|fim_middle|>Router
from .views import BookViewSet
rou | code_fim | easy | {
"lang": "python",
"repo": "rimvaliulin/termssrv",
"path": "/termssrv/terms/urls.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rimvaliulin/termssrv path: /termssrv/terms/urls.py
from rest_framework.routers import DefaultRouter
from .views import BookViewSet
rou<|fim_suffix|>ks', BookViewSet)
urlpatterns = router.urls<|fim_middle|>ter = DefaultRouter()
router.register('boo | code_fim | easy | {
"lang": "python",
"repo": "rimvaliulin/termssrv",
"path": "/termssrv/terms/urls.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>Solution --> linear reverse travel and save in a array and check in a the reverse
--> To linear reverse travel --> recurrsive function or save data in stack
Time --> 2O(n)
"""
llist = createfromlist([1, 2, 3, 4, 5, 6, 5, 4, 3, 2])
def checkpalindrome(head):
revlist.append(recsaverev(llist.head))
... | code_fim | hard | {
"lang": "python",
"repo": "RoKu1/cracking-the-coding-interview",
"path": "/Linked_Lists/6Palindrome.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RoKu1/cracking-the-coding-interview path: /Linked_Lists/6Palindrome.py
"""
Palindrome: Implement a function to check if a linked list is a palindrome,
"""
class Node:
def __init__(self, data):
self.data = data
self.next = None
class LList:
def __init__(self):
s... | code_fim | hard | {
"lang": "python",
"repo": "RoKu1/cracking-the-coding-interview",
"path": "/Linked_Lists/6Palindrome.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>"""
There are many solutions --> reverse the linkedlist and copy or save the reverse in array/stack(stack makes the linear
travesal reverse) or write recuursive function to save reverse -->
Solution --> linear reverse travel and save in a array and check in a the reverse
--> To linear reverse travel -->... | code_fim | hard | {
"lang": "python",
"repo": "RoKu1/cracking-the-coding-interview",
"path": "/Linked_Lists/6Palindrome.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KinglittleQ/GST-Tacotron path: /Synthesis.py
from utils import *
from Data import get_eval_data
from Hyperparameters import Hyperparameters as hp
import torch
from scipy.io.wavfile import write
from Network import *
import sys
import os
# import cv2
device = torch.device(hp.device)
def synth... | code_fim | hard | {
"lang": "python",
"repo": "KinglittleQ/GST-Tacotron",
"path": "/Synthesis.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> wav_hat = spectrogram2wav(mag_hat)
wav_path = os.path.join(log_dir, 'test_wav/epoch{}-{}.wav'.format(epoch, speaker))
write(wav_path, hp.sr, wav_hat)
print('synthesis ' + wav_path)
if __name__ == '__main__':
argv = sys.argv
log_number = int(argv[1])
epoch = in... | code_fim | hard | {
"lang": "python",
"repo": "KinglittleQ/GST-Tacotron",
"path": "/Synthesis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ## GCN related
parser.add_argument('--wup_pos', metavar='FLOAT', default=0.5, type=float,
help='threshold for positive relations')
parser.add_argument('--wup_neg', metavar='FLOAT', default=0.11, type=float,
help='threshold for... | code_fim | hard | {
"lang": "python",
"repo": "stevehuanghe/multi_label_zsl",
"path": "/utils/config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> parser.add_argument('--gcn_layers', metavar='STR', default='128 128', help='hidden layers')
parser.add_argument('--d_dim', metavar='INT', default=300, type=int, help='dimension for GCN input')
parser.add_argument('--h_dim', metavar='INT', default=64, type=int, help='dimension for a... | code_fim | hard | {
"lang": "python",
"repo": "stevehuanghe/multi_label_zsl",
"path": "/utils/config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stevehuanghe/multi_label_zsl path: /utils/config.py
import argparse
import yaml
from pprint import pprint
class ArgParser(object):
def __init__(self):
parser = argparse.ArgumentParser()
################################ Protected #####################################
p... | code_fim | hard | {
"lang": "python",
"repo": "stevehuanghe/multi_label_zsl",
"path": "/utils/config.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kowabunga314/lumen path: /lumen/showcase/tests.py
from datetime import datetime, timezone
from django.test import TestCase
from django.urls import resolve, reverse
from showcase.models import Photo, Series
from showcase.views import index, get_series
# Create your tests here.
class SeriesModelTe... | code_fim | hard | {
"lang": "python",
"repo": "kowabunga314/lumen",
"path": "/lumen/showcase/tests.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class SeriesApiTests(TestCase):
def test_series_basic_call(self):
response = self.client.get('/series/')
self.assertEqual(response.status_code, 200)
class PhotoApiTests(TestCase):
def test_photo_url_resolves(self):
response = self.client.get('/photo/')
self.asse... | code_fim | hard | {
"lang": "python",
"repo": "kowabunga314/lumen",
"path": "/lumen/showcase/tests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
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